Open-Brain

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions analysis types but doesn't describe what the tool actually does behaviorally - whether it performs computation, returns results immediately, requires specific data formats, or has any side effects. The description is essentially a list of analysis categories without explaining the tool's operational behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise - just 8 words listing analysis categories. It's front-loaded with 'Graph analysis' followed by specific types. While efficient, it may be overly terse given the complexity implied by the analysis categories. Every word serves a purpose in describing what the tool analyzes.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex-sounding analysis tool with no annotations and no output schema, the description is inadequate. It lists what gets analyzed but doesn't explain the tool's function, behavior, or results. Given the analytical nature and lack of structured documentation about outputs or side effects, the description should provide more context about what the tool actually does and returns.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description doesn't need to compensate for undocumented parameters, and the schema fully documents the input structure (though it's just 'additionalProperties: true'). No parameter information is needed in the description for this zero-parameter tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description lists specific analysis types (hubs, density, sources, etc.) which gives some indication of what the tool does, but it doesn't specify what resource or data it analyzes. The phrase 'Graph analysis' is somewhat vague without context about what kind of graph or data structure is being analyzed. It distinguishes from siblings by focusing on analysis rather than CRUD operations, but lacks a clear verb+resource combination.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided about when to use this tool versus alternatives. The description doesn't mention prerequisites, appropriate contexts, or when not to use it. While the analysis focus differentiates it from CRUD siblings like 'delete_thought' or 'update_thought', there's no explicit comparison to other analytical tools like 'thought_stats' or 'serendipity_digest'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.